A novel image compression technology based on vector quantisation and linear regression prediction
Shuying Xu, Chin‐Chen Chang, Yanjun Liu
Abstract
In the information age, a digital image is an important media for people’s daily interactions. Looking to maintain the quality of the restored image, how to maximise the compression of images has become a challenging topic. Vector quantisation (VQ) compression is an easy-operating image compression method that can compress images to 1/16th of the original size. Based on VQ compresses, a novel image compression method is proposed in this paper. The proposed scheme compresses the image depending on the result of linear regression prediction which can significantly increase the compression ratio.
Topics & Concepts
Image compressionComputer scienceData compressionArtificial intelligenceCompression (physics)Image (mathematics)Pattern recognition (psychology)Computer visionVector quantizationImage qualityCompression ratioDigital imageTexture compressionData compression ratioImage processingInternal combustion engineMaterials scienceEngineeringAutomotive engineeringComposite materialAdvanced Data Compression TechniquesImage and Signal Denoising MethodsAdvanced Image Processing Techniques